Your DORA metrics show a 30% change failure rate and long recovery times. How would you bring them down without slowing teams down?
What the interviewer wants to hear
- Analyse failed changes to find common causes
- Smaller batch sizes and trunk-based development
- Better automated tests and contract tests in the pipeline
- Progressive delivery and feature flags to limit blast radius
- Fast rollback, good observability and blameless postmortems
Model answer
First I would look at the data: which changes failed, in which services, and why, for example config errors, missing tests, schema changes or dependency issues. Usually large batches are a big cause, so I would push for smaller pull requests, trunk-based development and frequent deploys, which are easier to test and roll back. I would close test gaps found in the analysis, adding contract tests between services and checks for config and migrations in the pipeline. To limit impact, I would use canary releases with automated analysis and feature flags to separate deploy from release. For recovery time, rollback must be one click or automatic, with dashboards and alerts that point to the change that caused trouble. Blameless postmortems turn each failure into a pipeline or platform improvement. Speed and stability improve together this way.
Can you answer it under time pressure?
Take a timed hard round and get scored on every answer.
More hard DevOps Engineer questions
- You are asked to build an internal platform so 30 product teams can deploy services to Kubernetes on their own. How would you design it?
- How would you secure the software supply chain from source code to a running container in production?
- Your company wants to run a critical service active-active in two cloud regions. What are the main DevOps challenges and how would you handle them?
- How do you plan and carry out a Kubernetes version upgrade for production clusters with minimal risk?
- Leadership asks you to cut the cloud bill for your Kubernetes platform by 30 percent without hurting reliability. How do you approach it?
- You are the incident commander for a major outage affecting all customers. Describe how you run the incident from first page to postmortem.
- Design CI/CD for a monorepo with 60 services and 200 engineers where full builds take over an hour.
- Design a disaster recovery plan for a platform whose business requires an RTO of 1 hour and an RPO of 5 minutes for the loss of a whole cloud region.
- Several teams will share one Kubernetes cluster. How would you isolate tenants and secure the cluster?